Search By: SubjectAbstractAuthorTitleFull-Text


Showing 1 through 5 of 427 records.
Pages: Previous - 1 2 3 4 5 6 7 8 9 10 11 12 13 ... 86 - Next  Jump:
2007 - American Association of Colleges of Pharmacy Words: 265 words || 
1. Layson-Wolf, Cherokee., Trovato, James., Petrelli, Heather. and Morgan, Jill. "A scoring tool to standardize evaluation of applicants for admissions and to evaluate scores as predictors of success" Paper presented at the annual meeting of the American Association of Colleges of Pharmacy, Disney’s Yacht & Beach Club Resort, Lake Buena Vista, Florida, Jul 14, 2007 <Not Available>. 2018-11-17 <>
Publication Type: Abstract
Abstract: Purpose: The purpose of this project is the development and utilization of a new admission application scoring tool to evaluate applicants applying to the University of Maryland, School of Pharmacy. This tool allows the admissions committee to compare candidates based on a group of factors as opposed to single factors such as PCAT or GPA. Methods: The admissions committee identified five target areas that are of major importance when considering a pharmacy school applicant for interview. These five target areas included in the tool are: letters of recommendation, academic performance, PCAT score, work experience, and evidence of leadership. A four point scale was created for each area creating the highest potential score of 20, with 1 as the lowest rating, and 4 as the highest rating. Each candidate is evaluated according to their application packet and the information is utilized in the admissions review process. After the interview process, scores are included based on interview results. Total scores are utilized in the admissions decision process. For those admitted and entering the school, we will compare their tool scores to measures such as GPA to evaluate any relationship between scoring and academic performance. Conclusions: At the end of this admissions cycle, we would have utilized this screening tool for two years and will continue to refine our admissions process. For the coming years, we will utilize the data to compare scores of accepted candidates and performance in the first year of the curriculum.

2011 - North American Chapter of the International Group for the Psychology of Mathematics Education Pages: unavailable || Words: unavailable || 
2. Meylani, Rusen. and Teuscher, Dawn. "Using Neural-Networks to Predict AP-Calculus Test Scores from PCA and ACT Mathematics Test Scores" Paper presented at the annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, University of Nevada, Reno, Reno, NV, Oct 20, 2011 Online <APPLICATION/PDF>. 2018-11-17 <>
Publication Type: Poster
Review Method: Peer Reviewed
Abstract: Neural-Networks are a powerful alternative to regression especially for prediction and forecasting but not widely used in educational research. This study explores how AP-Calculus AB and BC scores can be predicted from the Precalculus Concept Assessment (PCA) and ACT mathematics scores employing two commonly used Neural-Networks models. Strong positive correlations between the actual and predicted values of the AP-Calculus exam scores confirm that Neural-Networks is an efficient tool for prediction. This can help identify the students who are at the risk of not passing the AP-Calculus exams and help students, parents and teachers take remedial measures in a timely manner.

2018 - Comparative and International Education Society Conference Words: 618 words || 
3. Alonge, Olusola. "Evidence based numeracy themed read alouds: Effect on EGMA scores, EGRA scores, and pupil interest in math" Paper presented at the annual meeting of the Comparative and International Education Society Conference, Hilton Mexico City Reforma Hotel, Mexico City, Mexico, <Not Available>. 2018-11-17 <>
Publication Type: Panel Paper
Abstract: Presenter: Olusola Alonge, Monitoring and Evaluation Specialist, Reading and Numeracy Activity (Organization: Achieving Health in Nigeria (AHNi) in partnership with FHI 360)
Title: Evidence based numeracy themed read alouds: effect on EGMA scores, EGRA scores, and pupil interest in math
Purpose: The purpose of this paper is to present how an innovative practice in mathematics instruction—teaching math through read aloud stories—may enhance math outcomes. The paper focuses on numeracy read aloud stories used in the DfID/UNICEF Reading and Numeracy Activity (RANA), implemented by FHI 360 in northern Nigeria.
Background: Mathematics researchers and practitioners have long recognized the need for reform in how mathematics is taught and learned. Ellis and Berry (2005) emphasize that methods of mathematics teaching must be expanded to encompass a wider variety of student needs, interests and learning styles. Of a variety of mathematics instructional strategies that have been proposed, the National Council of Teachers of Mathematics (1989) has noted that integrating math and literature is a promising strategy of bolstering math and language skills simultaneously.
In light of new trends that seek to broaden the teaching and learning of mathematics, RANA has implemented a set of Numeracy Read Aloud Stories (NRAS), which are designed to build math and oral language skills simultaneously. NRAS lessons include a math-themed story, which the teacher reads aloud, which is followed by listening comprehension questions and relevant math exercises. All NRAS are aligned with the Nigerian mathematics’ curriculum, with the aim of complementing pupils’ ongoing math classes.
RANA implements its read aloud classes as a complement to its regular phonics-based lessons. In the 2016-2017 schoolyear, RANA implemented two versions of the read aloud lesson. One version included read aloud stories with numeracy themes, while the other included regular (non-numeracy) read aloud stories. RANA evaluated the impact of these two versions against a control group, which received no read aloud intervention. RANA assessed the impact through observed effect on EGMA scores, EGRA scores, and a brief survey of pupil interest in math.
Methodology: In order to evaluate the impact of the NRAS on student-level reading and numeracy outcomes, RANA implemented a cluster randomized controlled trial (RCT) of P2 teachers at the school cluster level. The RCT had two treatment groups and a control group. In the first treatment group (25 percent of all school clusters), P2 teachers were trained to conduct a weekly lesson that entailed a language (Hausa) read-aloud without a numeracy theme. The second treatment group (25 percent of all school clusters), was comprised of P2 teachers who were trained to conduct a weekly lesson with the NRAS. Lastly, the remaining 50 percent of clusters and schools provided their P2 students with the same teaching curriculum as the treatment schools, but without read-aloud activities.
Results: At the end of the 2016-17 school year, we compared learning outcomes across the 3 groups to identify the impact of numeracy read alouds on oral reading fluency, listening comprehension, math word problems, number identification, and interest in math among P2 pupils. We find that students who were exposed to numeracy read alouds showed higher scores in oral reading fluency, listening comprehension, word problems, and interest in math. Students who were exposed to read alouds without a math theme showed improved scores in oral reading fluency and attitudes towards math, but not in word problems. As such, our study is able to show evidence that incorporating a numeracy element into read aloud stories may be an effective strategy for bolstering math outcomes.
Ellis, M. W., & Berry, R. Q. (2005). The paradigm shift in mathematics education: Explanations and implications of reforming conceptions of teaching and learning. Mathematics Educator, 15(1), 7-17.
National Council of Teachers of Mathematics (1989). Principles and standards for school mathematics. Retrieved from:

2018 - ICA's 68th Annual Conference Words: 342 words || 
4. Hearn, Alison. "Datafied Living and the ‘Citizen Score’: Credit Scoring, Soft Power and the Redefinition of Trust" Paper presented at the annual meeting of the ICA's 68th Annual Conference, Hilton Prague, Prague, Czech Republic, <Not Available>. 2018-11-17 <>
Publication Type: Session Paper
Abstract: When credit-reporting agency Equifax was hacked in July of 2017, news coverage predictably criticized the failure of the company’s cyber-security mechanisms, which left consumers vulnerable to increased levels of identity theft. No one commented on the conditions that produced this kind of vulnerability – the sheer breadth and depth of consumer data collected by Equifax – or on the ways automated credit-scoring systems have long worked to shape and privilege specific kinds of social identity in the first place. The coverage of the Equifax hack not only demonstrates the degree to which our datafied lives have become unremarkable, but also the extent to which we are now required to trust such computational practices even when they fail, or risk economic and cultural exclusion. Ian Bogost calls this cultural condition ‘computational theocracy’; while automation and datafication are deemed the height of rationality, they simultaneously demand absolute faith from everyday users in their procedures (Bogost, 2015). This form of techno-fetishism obscures both the material conditions of production behind datafication and the ways in which it is displacing traditional truth arbiters and radically redefining the meaning of trust itself. Nowhere is this more evident than in China’s recent plan to establish a countrywide ‘social credit system’, which will assign each citizen a numerical score based on their computed level of trustworthiness and ‘sincerity’. Marketed as a way to ‘forge a public opinion environment where keeping trust is glorious’ (Planning Outline, 2014), the citizen score will consider five dimensions of individual conduct derived from online data, including personal behavior and the quality of social networks. This paper will consider some of the potential effects of living with the ‘citizen score’ via an examination of one the most prominent prototypes being considered for use by the Chinese government – Sesame Credit. Proprietary practices of big data-driven analytics may demand our trust to accumulate capital and entrench new forms of soft political power, but, given their efforts to contain and control our life chances with little accountability or transparency, there is certainly no reason we should oblige them.

Pages: Previous - 1 2 3 4 5 6 7 8 9 10 11 12 13 ... 86 - Next  Jump:

©2018 All Academic, Inc.   |   All Academic Privacy Policy